Estimating the sediment trap efficiency of intermittently dry reservoirs: lessons from the Kruger National Park, South Africa

Reinwarth Bastian; Riddell Edward S.; Glotzbach Christoph; Baade Jussi

摘要

Abstract > The assessment of sediment yield from reservoir siltation requires knowledge of the reservoir's sediment trap efficiency (TE). Widely used approaches for the estimation of the long‐term mean TE rely on the ratio of the reservoir's storage capacity ( <fi>C</fi> ) to its catchment size ( <fi>A</fi> ) or mean annual inflow ( <fi>I</fi> ). These approaches have been developed from a limited number of reservoirs ( <fi>N</fi> ?≤?40), most of them located in temperate climate regions. Their general applicability to reservoirs receiving highly variable runoff such as in semi‐arid areas has been questioned. Here, we examine the effect of ephemeral inflow on the TE of 10 small (≤ 280?×?10 3 ?m 3 ), intermittently dry reservoirs located in the Kruger National Park. Fieldwork was conducted to determine the storage capacity of the reservoir basins. The frequency and magnitude of spillage events was simulated with the daily time step Pitman rainfall–runoff model. Different runoff scenarios were established to cope with uncertainties arising from the lack of runoff records and imperfect input data. Scenarios for the relationship between water and sediment discharge were created based on sediment rating curves. Taking into account uncertainties in hydrological modelling, uncertainties of mean TE estimates, calculated from all scenarios ( <fi>N</fi> ?=?9), are moderate, ranging from ±6 to ±11% at the 95% confidence level. By comparison, estimating TE from the storage capacity to catchment area ( <fi>C/A</fi> ) ratio induces high uncertainty (ranges of 35 to 65%), but this uncertainty can be confined (15 to 33%) when the latter approach is combined with hydrological mod </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> <div class="translation abstracttxt"> <span class="zhankaihshouqi fivelineshidden" id="abstract"> <span>机译：</span><abstract xmlns =“http://www.wiley.com/namespaces/wiley”type =“main”xml：lang =“en”> <title type =“main”>抽象</ title> >评估储层淤积的沉积物产量需要了解储层沉积物培养效率（TE）。广泛使用的方法来估计长期均值TE依赖于储库存储容量（<Fi> C </ Fi）的比例（<fi> a）（<fi> a </ fi>）或平均年度流入的比率（<fi> i </ fi>）。这些方法已从有限数量的储存器（<FI> N </ FI>？≤≤40）开发，其中大多数位于温带气候区。他们对接受高度变量径流的水库的一般适用性受到质疑。在这里，我们研究了10个小（≤280≤x≤10 3 </ sup> 3），间歇性的干燥水库位于克鲁格国家的干燥储存器公园。进行了实地工作以确定储层盆地的存储能力。利用日常时间步进皮特径径模型模拟溢出事件的频率和幅度。建立了不同的径流场景，以应对缺乏径流记录和不完美的输入数据引起的不确定性。基于沉积物级曲线创建了水和沉积物排放之间关系的情景。考虑到水文建模中的不确定性，根据所有场景计算的平均tE估计的不确定性（<fi> n </ fi> =Δ=Δ9），均为95％置信水平的±6至±11％。通过比较，从存储容量到集水区（<fi> c / a </ fi>）比率估计Te诱导高不确定性（范围为35到65％），但这种不确定性可以被限制（15至33％）后一种方法与水文MOD结合 </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> </div> <div class="record"> <h2 class="all_title" id="enpatent33" >著录项</h2> <ul> <li> <span class="lefttit">来源</span> <div style="width: 86%;vertical-align: text-top;display: inline-block;"> <a href='/journal-foreign-22319/'>《Earth Surface Processes and Landforms: The journal of the British Geomorphological Research Group》</a> <b style="margin: 0 2px;">|</b><span>2018年第2期</span><b style="margin: 0 2px;">|</b><span>共19页</span> </div> </li> <li> <div class="author"> <span class="lefttit">作者</span> <p id="fAuthorthree" class="threelineshidden zhankaihshouqi"> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Reinwarth Bastian&option=202" target="_blank" rel="nofollow">Reinwarth Bastian;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Riddell Edward S.&option=202" target="_blank" rel="nofollow">Riddell Edward S.;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Glotzbach Christoph&option=202" target="_blank" rel="nofollow">Glotzbach Christoph;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Baade Jussi&option=202" target="_blank" rel="nofollow">Baade Jussi;</a> </p> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zkzz" style="display: none;">展开▼</span> </div> </li> <li> <div style="display: flex;"> <span class="lefttit">作者单位</span> <div style="position: relative;margin-left: 3px;max-width: 639px;"> <div class="threelineshidden zhankaihshouqi" id="fOrgthree"> <p>Department of GeographyFriedrich Schiller UniversityJena Germany;</p> <p>Centre for Water Resources ResearchUniversity of KwaZulu‐NatalScottsville Pietermaritzburg South Africa;</p> <p>Department of GeosciencesUniversity of TübingenTübingen Germany;</p> <p>Department of GeographyFriedrich Schiller UniversityJena Germany;</p> </div> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zhdw" style="display: none;">展开▼</span> </div> </div> </li> <li > <span class="lefttit">收录信息</span> <span style="width: 86%;vertical-align: text-top;display: inline-block;"></span> </li> <li> <span class="lefttit">原文格式</span> <span>PDF</span> </li> <li> <span class="lefttit">正文语种</span> <span>eng</span> </li> <li> <span class="lefttit">中图分类</span> <span><a href="https://www.zhangqiaokeyan.com/clc/163.html" title="地球物理学">地球物理学;</a></span> </li> <li class="antistop"> <span class="lefttit">关键词</span> <p style="width: 86%;vertical-align: text-top;"> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=reservoir siltation&option=203" rel="nofollow">reservoir siltation;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=sediment retention&option=203" rel="nofollow">sediment retention;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=episodic spillage&option=203" rel="nofollow">episodic spillage;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Pitman model&option=203" rel="nofollow">Pitman model;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=sediment rating curve&option=203" rel="nofollow">sediment rating curve;</a> </p> <div class="translation"> 机译：储层淤积;沉积物保留;情节溢出;皮特曼模型;沉积物曲线; 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